Markers of environmental enteric dysfunction are associated with poor growth and iron status in rural ugandan infants

Background: Environmental enteric dysfunction (EED), characterized by altered intestinal permeability/inflammation, microbial translocation, and systemic inflammation (SI), may be a significant contributor to micronutrient deficiencies and poor growth in infants from low-resource settings. Objective: We examined associations among EED, SI, growth, and iron status at 6 mo of age. Methods: We performed a cross-sectional analysis of 6-mo-old infants (n = 548) enrolled in a Ugandan birth-cohort study (NCT04233944). EED was assessed via serum concentrations of anti-flagellin and anti- LPS immunoglobulins (Igs); SI was assessed via serum concentrations of a1-acid glycoprotein (AGP) and C-reactive protein (CRP); iron status was assessed via serum concentrations of hemoglobin (Hb), soluble transferrin receptor (sTfR), and ferritin. Associations were assessed using adjusted linear regression analysis. Results: At 6 mo, ∼35% of infants were stunted [length-for-age z score (LAZ) < −2] and ∼53% were anemic [hemoglobin (Hb) <11.0 g/dL]. Nearly half (∼46%) had elevated AGP (>1 g/L) and ∼30% had elevated CRP (>5 mg/L). EED and SI biomarkers were significantly correlated (r = 0.142-0.193, P < 0.001 for all). In adjusted linear regression models, which included adjustments for SI, higher anti-flagellin IgA, anti-LPS IgA, and anti-LPS IgG concentrations were each significantly associated with lower LAZ [β (95% CI): −0.21 (−0.41, 0.00), −0.23 (−0.44, −0.03), and −0.33 (−0.58, −0.09)]. Furthermore, higher anti-flagellin IgA, anti-flagellin IgG, and anti-LPS IgA concentrations were significantly associated with lower Hb [β (95% CI): −0.24 (−0.45, −0.02), −0.58 (−1.13, 0.00), and −0.26 (−0.51, 0.00)] and higher anti-flagellin IgG and anti-LPS IgG concentrations were significantly associated with higher sTfR [β (95% CI): 2.31 (0.34, 4.28) and 3.13 (0.75, 5.51)]. Conclusions: EED is associated with both low LAZ and iron status in 6-mo-old infants. Further research on the mechanisms by which EED affects growth and micronutrient status is warranted. Study approval was obtained from the Makerere University Research Ethics Committee at the School of Public Health in Kampala, Uganda; the Uganda National Council for Science and Technology in Kampala, Uganda; the Tufts Health Sciences Institutional Review Board in Boston, Massachusetts; and the Harvard TH Chan School of Public Health Institutional Review Board in Boston, Massachusetts. Written consent was obtained from all mothers prior to enrollment. Participants in this observational, cross-sectional study were a subset of infants enrolled in a birth-cohort study, the Uganda Birth Cohort Study (UBCS; {"type":"clinical-trial","attrs":{"text":"NCT04233944","term_id":"NCT04233944"}}NCT04233944). The UBCS, which was conducted from 2014 to 2016 by the US Agency for International Development (USAID) Feed the Future Innovation Lab for Nutrition at Tufts University, recruited and followed ∼5000 pregnant women in 16 subcounties in rural southwestern (Bugangari, Buyanja, Bwizi, Kebisoni, Kibiito, Nyamweru, Rugyeyo, and Ruhija) and northern (Aduku, Agoro, Agweng, Apac, Atanga, Atyak, Ayer, and Parombo) Uganda. Home visits were conducted every 3 mo from pregnancy until the infant turned 6 mo of age. Extensive household, maternal, and infant data were collected within the UBCS, including in-depth information on demographics, household characteristics, agricultural production, WASH practices, food security [using the Household Food Insecurity Access Scale (HFIAS)] (34), nutritional and health status of women through pregnancy, birth outcomes, and anthropometry for women and their infants. Maternal height and infant length were measured to the nearest 0.1 cm using a portable height board (ShorrBoard® infant/child/adult portable height-length measuring board; Weigh and Measure, LLC); weight was measured to the nearest 0.1 kg using an electronic scale (Seca model 874; Seca Corporation). All anthropometry measurements were taken in triplicate and averaged. Hb concentrations were measured at 6 mo of age using a finger-prick blood sample and a portable hemoglobinometer (HemoCue 301; HemoCue America). Blood samples for biomarker analysis were collected via venipuncture by a trained phlebotomist (BD Vacutainer; Becton Dickinson). Samples were then transported on ice to facility laboratories, where serum was separated, placed into aliquots, and frozen at −20°C. The flow diagram for the study is presented in Figure 1. Of the 5044 households enrolled in the UBCS, 1700 had a maternal serum sample collected at birth and an infant sample collected at 6 mo of age. From these, infant serum samples from the 6-mo visit with adequate sample volume (n = 781) were selected and analyzed for anti-flagellin and anti-LPS Igs; 688 were further analyzed for biomarkers of SI and iron status. Infants missing 6-mo covariate/anthropometry data (n = 140) were excluded from analysis. A total of 548 infants were therefore included in this study. Of these, 488 infants had Hb assessed at 6 mo of age. Flow diagram for cross-sectional study of infants from northern and southwestern Uganda. EED, environmental enteric dysfunction; SI, systemic inflammation; UBCS, Uganda Birth Cohort Study. Serum samples were analyzed for concentrations of anti-flagellin and anti-LPS IgA and IgG at Georgia State University (Atlanta, GA) via previously described ELISA methods (25). Briefly, serum samples were diluted 1:200 and applied to wells coated with either flagellin (100 ng/well) or LPS (2 μg/well). Wells were then incubated with anti-human IgA (KPL) or IgG (GE Healthcare) coupled to HRP. The quantification of total Igs was conducted using the colorimetric peroxidase substrate tetramethylbenzidine, and absorbance [optical density (OD)] was read at 450 nm using an ELISA plate reader. Concentrations of serum biomarkers are reported as OD-corrected data; higher values suggest increased intestinal permeability and microbial translocation indicative of EED. Samples were further analyzed for AGP, CRP, sTfR, and ferritin at the VitMin Lab in Willstaett, Germany, via previously described sandwich ELISA methods (35). Ferritin and sTfR were adjusted for inflammation using the Biomarkers Reflecting Inflammation and Nutritional Determinants of Anemia (BRINDA) method (36). Background characteristics, including household, maternal, and infant characteristics, were calculated and presented as means ± SDs or n (%) for continuous and categorical outcomes, respectively. Growth outcomes at 6 mo of age, including LAZ, WAZ, and WLZ, were calculated using the WHO Multicenter Growth Reference Study growth standards (1). Outliers, defined as LAZ <6 or ≥6, WAZ <6 or ≥5, and WLZ <5 or ≥5, were set to missing. EED, SI, and iron status biomarker concentrations are presented as medians (IQRs). Mann-Whitney U tests were used to assess differences in biomarker concentrations between moderately (< −2 to ≥ −3 SDs) and severely (< −3 SDs) stunted infants and infants ≥ −1 SD. Because of their skewed distribution, EED and SI biomarkers were ln-transformed prior to correlation and regression analyses. Pearson correlation coefficients were calculated to assess relations between EED biomarkers (anti-flagellin and anti-LPS IgA and IgG) and SI biomarkers (AGP and CRP). Adjusted linear regression models were used to assess the association between EED and SI biomarkers and infant growth. Adjusted models controlled for significant predictors of LAZ at 6 mo of age (P < 0.10 in unadjusted analyses), including maternal age, maternal height, household head educational level, infant sex, infant birth weight, household food security status (HFIAS), improved water source (yes/no), AGP (EED models only), and subcounty clustering. Finally, adjusted linear regression models, controlling for infant sex, age, and subcounty clustering, were developed to assess the association between EED biomarkers and iron status biomarkers, including Hb (grams/deciliter), inflammation-adjusted sTfR (milligrams/liter), and inflammation-adjusted ferritin (micrograms/liter). All statistical analyses were carried out using STATA 15 software (StataCorp). For all analyses, a P value <0.05 was considered statistically significant.